Findly

Freemium

Turn questions into insights: Findly AI makes your data conversational.

#AI#analytics#data visualization#database querying#NLG#natural language generation#forecasting#report generation#business insights#Slack integration#Teams integration#semantic layer#SQL connectors#marketing platforms#cloud platforms

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Starting Price

$149/mo

Type

Saas

Company

Findly

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About Findly

Findly is an AI-powered chatbot that simplifies data access for every team member, providing accurate and actionable data insights in minutes without the need for SQL or Python expertise. Its flexible architecture integrates with various databases, including Google BigQuery, PostgreSQL, Snowflake, and Amazon Redshift, ensuring maximum privacy and security. Findly also offers AI data analysis tools and machine learning for businesses, enabling data management, reporting, and business insights through cutting-edge machine learning for data visualization and analytics.

How to Use

Start using Findly by connecting your databases and communicating with your data. Integrate Findly on Slack for seamless access. Visualize query results and export data in various formats.

Key Features

AI-powered data analysis
Database integration
Data visualization
Report generation
Slack integration
Semantic layer model
Real-time analytics

Use Cases

Trading Intelligence: Forecast commodity prices, track cargos, manage risks.
Supply Chain Optimization: Optimize logistics, plan routes, ensure timely deliveries.
Energy Trading: Forecast oil prices, manage risks.
Consulting Business: Provide AI-driven solutions for pricing and market launches.
Retail & Ecommerce: Discover hidden trends, optimize operations.

Key Features

Natural language query interface powered by advanced ML and LLMs

AI-powered query generator for real-time insights

Real-time analytics with KPI monitoring and drill-down visualizations

Customizable dashboards and automated report generation

Report scheduling and exports to PDF, Excel, and PowerPoint

Slack and Microsoft Teams integration for in-chat analytics

Seamless data integrations: any SQL, Google Analytics, Facebook Ads, Shopify Ads, Google Search Console, BigQuery, Google Cloud

AI-driven forecasting for trends, pricing, operations, supply chain, and risk

Semantic layer for unified definitions and consistent metrics

Security and compliance: SOC 2 Type II and ISO 27001

Pros & Cons

Pros

Natural language query eliminates the need for SQL or Python skills, making data accessible to all team members.
Integrates with major data sources and business tools including Google Analytics, Facebook Ads, SQL databases, Slack, and Teams.
Real-time analytics and automated report generation save hours of manual work.
AI-driven forecasting helps teams anticipate trends and make proactive decisions.
Semantic layer ensures consistent definitions and metrics across the organization, reducing confusion.
Enterprise-grade security (SOC 2 Type II, ISO 27001) suitable for regulated industries.
Scalable from small teams with a free plan to large enterprises with unlimited users.
Supports multiple languages, broadening global team usability.

Cons

Free plan limited to 3 users and only Google Analytics and Facebook Ads integrations.
Standard plan ($149/month) still limited to 10 users, which may not fit larger teams.
Dependence on AI model accuracy may require validation for critical business decisions.
Advanced features like white-labeling, embedded assistant, and on-premise deployment only available on Enterprise plan (pricing undisclosed).
Setting up the semantic layer and custom integrations may require initial guidance from support.

Best For

Marketing leaders: Track campaign ROI across Google Analytics, Facebook Ads, and Shopify Ads and auto-generate weekly performance reports.Sales ops: Analyze pipeline health, win rates, and forecast revenue by simply asking questions over CRM and SQL data.Finance teams: Monitor cash flow, variance to plan, and generate real-time P&L snapshots with automated report scheduling.Operations managers: Forecast demand, optimize inventory, and surface supply chain risks with AI-driven predictions.Product managers: Explore funnels, retention, and feature adoption from product databases or BigQuery using natural language queries.Executives: Receive KPI briefings and drill-down visualizations directly in Slack or Teams for fast, informed decisions.Customer support leaders: Analyze ticket volume, resolution times, and sentiment trends and share insights in chat for rapid action.E-commerce managers: Visualize SKU performance, margins, and cohort LTV while automating daily sales summaries.Risk and compliance: Detect anomalies, monitor thresholds, and trigger alerts with real-time analytics and reporting.BI and data teams: Define a semantic layer, enable governed self-service analytics, and standardize metrics across the business.